Triple
T8206805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Costa da Morte |
E191707
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Corme
Corme is a coastal village in Galicia, northwestern Spain, known for its fishing heritage and dramatic Atlantic scenery along the Costa da Morte.
|
E719451
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Corme | Statement: [Costa da Morte, contains, Corme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Corme Context triple: [Costa da Morte, contains, Corme]
-
A.
L’Arc
L’Arc is one of the monumental postmodern residential structures within Ricardo Bofill’s Les Espaces d'Abraxas complex in Noisy-le-Grand, France.
-
B.
Orcet
Orcet is a small commune in the Puy-de-Dôme department of central France, known as the birthplace of French revolutionary figure Georges Couthon.
-
C.
Komen
Komen is the surname associated with Susan G. Komen, whose name is borne by a major U.S. breast cancer advocacy and research organization.
-
D.
Komen
Komen is a municipality in western Slovenia’s Littoral region, known for its karst landscape and proximity to the Italian border.
-
E.
Enide
Enide is a heroine of Arthurian romance, best known as the loyal and courageous wife of the knight Erec in medieval French literature.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Corme Triple: [Costa da Morte, contains, Corme]
Generated description
Corme is a coastal village in Galicia, northwestern Spain, known for its fishing heritage and dramatic Atlantic scenery along the Costa da Morte.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Corme Target entity description: Corme is a coastal village in Galicia, northwestern Spain, known for its fishing heritage and dramatic Atlantic scenery along the Costa da Morte.
-
A.
L’Arc
L’Arc is one of the monumental postmodern residential structures within Ricardo Bofill’s Les Espaces d'Abraxas complex in Noisy-le-Grand, France.
-
B.
Orcet
Orcet is a small commune in the Puy-de-Dôme department of central France, known as the birthplace of French revolutionary figure Georges Couthon.
-
C.
Komen
Komen is the surname associated with Susan G. Komen, whose name is borne by a major U.S. breast cancer advocacy and research organization.
-
D.
Komen
Komen is a municipality in western Slovenia’s Littoral region, known for its karst landscape and proximity to the Italian border.
-
E.
Enide
Enide is a heroine of Arthurian romance, best known as the loyal and courageous wife of the knight Erec in medieval French literature.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb726b520081908ce4a03bd14dfcdf |
completed | March 31, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccedda69148190b8c221221de5dae5 |
completed | April 1, 2026, 10:05 a.m. |
| NEDg | Description generation | batch_69ccf1ba74548190831677bb126bea1a |
completed | April 1, 2026, 10:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd05c2059081908bd04ee4722f9aad |
completed | April 1, 2026, 11:47 a.m. |
Created at: March 30, 2026, 5:43 p.m.